Data Scientist
A data engineering-focused role (posted under a Data Scientist title) designing and delivering large-scale cloud data pipelines and warehouse/lakehouse solutions for airline clients. Day to day: Databricks, Spark/PySpark, Delta Lake, Snowflake, AWS/Azure, Python/SQL/Scala, Airflow, MLflow and BI tooling.
- Compensation
- Not disclosed
- Location
- Bucharest, Bucharest, Romania
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 1+ years
- Category
- Data science
- Posted
Skills
Must have
- At least 5 years of experience in Data Engineering or a related field
- Minimum 1 year hands-on experience with Databricks in a production environment
- Strong expertise in cloud platforms (e.g. AWS, Azure, GCP), Data Lake technologies and Data Warehousing
- Experience with data ETL tools and BI solutions (e.g. Airflow, PowerBI)
- Experience with data quality and governance tools (e.g. Atlan, Monte Carlo)
- Solid knowledge of data modelling concepts
- Hands-on experience in Databricks, Spark, PySpark and Delta Lake
- Practical MLOps experience, ideally with MLflow
- Strong knowledge of AWS, with Azure experience advantageous for multi-cloud setups
- Advanced coding abilities in Python, SQL and Scala
- Familiarity with GitHub, CI/CD tools (Azure DevOps, GitHub Actions), orchestration (Airflow, Jenkins) and dashboarding tools (Tableau, Alteryx)
- Excellent communication and collaboration skills
- Problem-solving and analytical mindset
- Ability to work autonomously and as part of a team
Nice to have
- Master's in Computer Science, Data Science or a related field
- Proven experience designing and implementing complex data pipelines and data warehouse solutions in an enterprise environment
- Experience with Scaled Agile planning and execution
Full description
About us:
Amach is an industry-leading technology driven company with headquarters located in Dublin and remote teams in UK and Europe.
Our blended teams of local and nearshore talent are optimised to deliver high quality and collaborative solutions.
Founded in 2013, Amach was created to solve a specific problem in aviation: too much complexity, too little usable intelligence. We help airlines modernise their operating model using cloud, data and Al-delivered by teams with deep aviation domain expertise.
Our goal is to maximize airlines' operational efficiency by optimizing resource use, reduce costs and increase customer experience and satisfaction.
The Senior Data Engineer is a highly skilled data management specialist in charge of developing and implementing complex data pipelines and data warehouse solutions. They will work closely with data engineers, architects and product owners to ensure high-quality delivery of Data Assets.
Required Experience:
- At least 5 years of experience in Data Engineering or a related field
- A minimum of 1 years of hands-on experience with Databricks in a production environment
- Strong expertise in cloud platforms (e.g. AWS, Azure, GCP), Data Lake technologies and Data Warehousing
- Experience with data ETL tools and BI solutions (e.g., Airflow, PowerBI)
- Experience with data quality and governance tools (e.g., Atlan, Monte Carlo)
- Solid knowledge of data modelling concepts
- Excellent communication and collaboration skills
- A problem-solving and analytical mindset
- Ability to work autonomously and as part of a team
Key responsibilities & duties include:
- Data Engineering Expertise: Proven experience in architecting and delivering large-scale, cloud-native data solutions
- Advanced Knowledge in Databricks and Snowflake: Hands-on experience in Databricks, Spark, Pyspark and Delta Lake, with strong skills in data warehousing and lakehouse solutions
- MLOps Skills: Practical experience in MLOps, ideally with MLflow for model management and deployment
- Cloud Proficiency: Strong knowledge of AWS, with additional experience in Azure advantageous for multi-cloud setups
- Programming Proficiency: Advanced coding abilities in Python, SQL and Scala
- Tooling Competence: Familiarity with version control (GitHub), CI/CD tools (Azure DevOps, GitHub Actions), orchestration tools (Airflow, Jenkins) and dashboarding tools (Tableau, Alteryx)